Abstract

Preterm neonates face significant neurological risks due to incomplete brain development at birth. The third trimester is critical for brain maturation, and premature birth disrupts essential developmental processes, leading to long-term cognitive, motor, and sensory impairments. Key vulnerabilities include cortical underdevelopment, white matter damage, and immature neurotransmission, contributing to neurodevelopmental disorders such as cerebral palsy, attention deficits, and learning difficulties. While advances in Neonatal Intensive Care Units (NICUs) have improved survival rates, early detection and continuous monitoring of complications remain challenging. The integration of Internet of Things (IoT) technology in neonatal care presents a transformative approach, enabling real-time physiological monitoring, predictive analytics, and automated alerts for timely interventions. IoT-driven neonatal monitoring systems enhance clinical decision-making, reduce caregiver burden, and improve patient outcomes. In parallel, Artificial Intelligence (AI) is revolutionizing neonatal healthcare by processing multimodal data, including clinical records, physiological signals, and imaging to provide real-time insights, predictive diagnostics, and risk assessments. Machine learning (ML) and deep learning (DL) techniques aid in disease prediction, anomaly detection, and precision diagnostics, significantly enhancing neonatal monitoring. However, challenges such as AI interpretability, data security, and integration into clinical workflows must be addressed to ensure adoption. Explainable-AI (XAI) tools such as SHAP, LIME, and Grad-CAM are crucial in making AI-driven decisions more transparent and actionable. The future of neonatal AI lies in developing multimodal frameworks that integrate physiological signals and facial, vocal, and motion data for comprehensive neonatal health monitoring. Addressing the technical and ethical challenges associated with AI and IoT adoption will be critical to fully realizing their potential in neonatal care and improving outcomes for preterm infants.